This program works for me.
Have you updated Stata recently?
______________________________________________
Kieran McCaul MPH PhD
WA Centre for Health & Ageing (M573)
University of Western Australia
Level 6, Ainslie House
48 Murray St
Perth 6000
Phone: (08) 9224-2140
Fax: (08) 9224 8009
email: [email protected]
http://myprofile.cos.com/mccaul
_______________________________________________
The fact that no one understands you doesn't make you an artist.
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Victor M.
Zammit
Sent: Friday, 14 November 2008 8:38 AM
To: [email protected]
Subject: Re: st: Re: Memory
When I tried that program I got the error : "option gweight not allowed
"
and then I gave up on it .What can I do to avoid getting that error?
. capture prog drop makez
. prog makez, rclass
1. syntax [, obs(integer 31)]
2. clear
3. set obs `obs'
4. gen a = invnorm(uniform())
5. ttest a=0
6. return scalar t=r(t)
7. end
. simul, reps(100000) seed(123): makez
option gweight not allowed
r(198);
----- Original Message -----
From: "Austin Nichols" <[email protected]>
To: <[email protected]>
Sent: Thursday, November 13, 2008 7:27 PM
Subject: Re: st: Re: Memory
> Victor M. Zammit <[email protected]>:
> I don't understand this reply at all. Did you try the simulation
> approach? It takes very little memory:
>
> Contains data from \t.dta
> obs: 100,000 simulate: makez
> vars: 1 13 Nov 2008 11:04
> size: 1,200,000 (99.9% of memory free)
>
> g d=0
> replace d=1.31 if t>1.31
> replace d=1.697 if t>1.697
> replace d=2.042 if t>2.042
> replace d=2.457 if t>2.457
> replace d=2.75 if t>2.75
> tab d
>
> d | Freq. Percent Cum.
> ------------+-----------------------------------
> 0 | 90,017 90.02 90.02
> 1.31 | 4,974 4.97 94.99
> 1.697 | 2,441 2.44 97.43
> 2.042 | 1,523 1.52 98.95
> 2.457 | 552 0.55 99.51
> 2.75 | 493 0.49 100.00
> ------------+-----------------------------------
> Total | 100,000 100.00
>
> _pctile t, nq(100)
> ret li
>
> r(r99) = 2.475399255752564
> r(r95) = 1.697941184043884
> r(r90) = 1.30941379070282
>
>
> On Thu, Nov 13, 2008 at 12:21 PM, Victor M. Zammit <[email protected]>
wrote:
> > t-table.I understand that you need a number of random tries ,much
bigger
> > than that of forty thousand,to come to convergence.So I was
wondering
if
> > that that constraint with memory ,could be handled.
> >
> >
> > ----- Original Message -----
> > From: "Austin Nichols" <[email protected]>
> > To: <[email protected]>
> > Sent: Thursday, November 13, 2008 4:09 PM
> > Subject: Re: st: Re: Memory
> >
> >
> >> Victor M. Zammit:
> >> I also don't understand the point of this exercise--but you should
> >> read -help simul- and try e.g.
> >>
> >> prog makez, rclass
> >> syntax [, obs(integer 31)]
> >> clear
> >> set obs `obs'
> >> gen a = invnorm(uniform())
> >> ttest a=0
> >> return scalar t=r(t)
> >> end
> >> simul, reps(100000) seed(123): makez
> >>
> >>
> >> On Thu, Nov 13, 2008 at 9:56 AM, Nick Cox <[email protected]>
wrote:
> >> > I still don't understand what you are trying to do. But I can
comment
on
> >> > your code.
> >> >
> >> > You are looping round 40,000 times and writing a single result to
40,000
> >> > data files. Then you are looping round to put all those 40,000
data
> >> > files in one.
> >> >
> >> > I'd do that directly this way using just one extra file:
> >> >
> >> > clear
> >> > set obs 31
> >> > gen a = .
> >> > tempname out
> >> > postfile `out' t using myresults.dta
> >> > qui forval i = 1/40000 {
> >> > replace a = invnorm(uniform())
> >> > ttest a = 0
> >> > post `out' (r(t))
> >> > }
> >> > postclose `out'
> >> >
> >> > I still doubt 40,000 is anywhere big enough to get an answer.
> >> >
> >> > Nick
> >> > [email protected]
> >> >
> >> > Victor M. Zammit
> >> >
> >> > * a} The data that I have is from generating random samples of
whatever
> >> > size,in this case of size 31,from a normally
distributed,infinitely
> >> > large,
> >> > population; ie
> >> >
> >> > local i = 1
> >> >
> >> > while `i'<= 40000 {
> >> >
> >> > drop _all
> >> >
> >> > set obs 31
> >> >
> >> > gen a = invnorm(uniform())
> >> >
> >> > qui ttest a = 0
> >> >
> >> > replace a = r(t) in 1
> >> >
> >> > keep in 1
> >> >
> >> > save a`i',replace
> >> >
> >> > local i = `i'+1
> >> >
> >> > }
> >> >
> >> > * I use 40000 due to memory constraint.Appending the a[i]'s
together
> >> > gives
> >> > me a variable of 40000 observations ,ie
> >> >
> >> > use a1,clear
> >> >
> >> > local i = 2
> >> >
> >> > while `i'<= 40000 {
> >> >
> >> > append using a`i'.dta
> >> >
> >> > local i = `i'+1
> >> >
> >> > }
> >> >
> >> > save ais40000,replace
> >> >
> >> > * b) From ais40000.dta I get the density <= 1.31, presumably to
get
the
> >> > density of 90% , <= 1.697 to get the density of 95% etc
etc,according
to
> >> > the
> >> > official ttable, ie
> >> >
> >> > capture program drop density
> >> >
> >> > program define density
> >> >
> >> > use ais40000,clear
> >> >
> >> > count if a<= `1'
> >> >
> >> > di " density >=" "`1'" " = " r(N)/40000
> >> >
> >> > end
> >> >
> >> > density 1.31
> >> >
> >> > density 1.697
> >> >
> >> > density 2.042
> >> >
> >> > density 2.457
> >> >
> >> > density 2.75
> >> >
> >> > * For smaller degrees of freedom,the discrepancy is much higher.I
would
> >> > like
> >> > to know how if it is at all possible to resolve memory constraint
.
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
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*
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